Abstract
The rise of online social media has led to an explosion in user-generated content. However, user-generated content is difficult to analyze in isolation from its context. Accordingly, context detection and tracking its evolution is essential to understanding social media. This paper presents a statistical model that can detect interpretable topics along with their contexts. A topic is represented by a cluster of words that frequently occur together, and a context is represented by a cluster of hashtags that frequently occur with a topic. The model combines a context with a related topic by jointly modeling words with hashtags and time. Experiments on real datasets demonstrate that the proposed model successfully discovers both meaningful topics and contexts, and tracks their evolution.
Original language | English |
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Title of host publication | DUBMOD 2014 - Proceedings of the 3rd Workshop on Data-Driven User Behavioral Modeling and Mining from Social Media, co-located with CIKM 2014 |
Publisher | Association for Computing Machinery |
Pages | 15-18 |
Number of pages | 4 |
Edition | November |
ISBN (Electronic) | 9781450313032, 9781450316064 |
DOIs | |
Publication status | Published - 2014 Nov 3 |
Event | 3rd Workshop on Data-Driven User Behavioral Modeling and Mining from Social Media, DUBMOD 2014, Co-located with 23rd ACM Conference on Information and Knowledge Management, CIKM 2014 - Shanghai, China Duration: 2014 Nov 3 → … |
Publication series
Name | International Conference on Information and Knowledge Management, Proceedings |
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Number | November |
Volume | 2014-November |
Other
Other | 3rd Workshop on Data-Driven User Behavioral Modeling and Mining from Social Media, DUBMOD 2014, Co-located with 23rd ACM Conference on Information and Knowledge Management, CIKM 2014 |
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Country/Territory | China |
City | Shanghai |
Period | 14/11/3 → … |
Bibliographical note
Publisher Copyright:Copyright © 2014 by the Association for Computing Machinery, Inc. (ACM).
Keywords
- Context and topic evolution
- Social media
- Topic model
ASJC Scopus subject areas
- General Business,Management and Accounting
- General Decision Sciences